LoRa rescue: Emergency distress signal geolocation system - Pe, Gregory James G. (Animo Repository, 2021)
In a calamity, cellular networks, internet services, and electricity may prove to be unreliable. And yet, emergency responders will need a way to contact and locate people-in-need as soon as possible. As such, this thesis proposes an emergency trilateration system that uses LoRa. A wireless communications technology characterized by its longer range and lower power consumption compared to other technologies such as Bluetooth and WiFi. This thesis developed a LoRa trilateration algorithm that improves upon the standard trilateration algorithm by using the closest points. This improved trilateration algorithm obtained a 73.0185% improvement in accuracy compared to the standard algorithm, across 25 datasets. Furthermore, the thesis utilized automated elbow methods to acquire the optimal parameters required by the DBSCAN and K-means clustering algorithms. For DBSCAN, the study automated the acquisition of the Epsilon and MinPts parameters, and for K-means, the SoSD parameter. After applying these clustering algorithms to filter the data, the results provided an average error of 39.6506 meters from the actual position.